One of the major characteristics of conventional motion compensated hybrid video codecs is use of translational model for motion description. Pixel value of a digital video sequence represents the light intensity from certain object that falls into the detection range of some discrete sensor. Since an object motion is completely unrelated to the sampling grid, sometimes the object motion is more like a fractional-pel motion than a full-pel one. Therefore, most modern hybrid video coding standards use fractional-pel displacement vector resolution of ½-pel or ¼-pel.
In order to estimate and compensate fractional-pel displacements, the image signal on these fractional-pel positions has to be generated by interpolation process. The taps of an interpolation filter weight the integer pixels in order to generate the fractional-pel signals. The simplest filter for fractional-pel signal interpolation is bilinear filter, but there is no improvement beyond ⅛-pel (See Cliff Reader, “History of MPEG Video Compression”, JVT of ISO/IEC MPEG and ITU-T VCEG, Docs. JVT-E066, October 2002). Therefore, only ½-pel resolution using bilinear interpolation is adopted in MPEG-2 and H.263.
Werner supposes the reason for poor performance of bilinear filter is that the Nyquist Sampling Theorem is not fulfilled and aliasing disturbs the motion compensated prediction. He proposes Wiener interpolation filters for reducing the impact of aliasing (See O. Werner, “Drift analysis and, drift reduction for multiresolution hybrid video coding,” Signal Processing: Image Commun., vol. 8, no. 5, July 1996). Thus, recent video coding standards like MPEG-4 part 2 and H.264 apply 8-tap and 6-tap Wiener interpolation filters respectively. These filters are obtained by solving the Wiener-Hopf equations. The equations should be specified for filters with different filter length and the resultant taps are limited within a range while different video sequences are used as the input signals.
Generally, the interpolation process is realized by using weighted sum of the integer pixels to calculate the target fractional pixel values. A practical implementation is to use non-zero integer values as the weighting factors and apply right shift to save computational complexity with added shift offset. Clip operation might also be applied to keep the interpolated pixel values within the normal dynamic range.
Traditionally, the half-pel interpolation process uses an even number of integer pixels symmetric around a current half-pel position. The interpolation process for nearby quarter-pel or eighth-pel pixels employs the same set of integer pixels. This constraint on fractional-pel interpolation process is actually not necessary. Releasing this constraint can make the filter design more flexible, thus achieving better performance and/or lower complexity.